Summary
Manmeet Singh is a geo-data scientist and Assistant Professor with a decade of experience at the intersection of Earth system modeling, nonlinear dynamics, and AI-driven climate science. He develops and applies deep learning and diffusion-based methods for high-resolution weather and soil-moisture forecasts, and has built AI-augmented models for subseasonal-to-seasonal prediction and specialized components for atmosphere, land, and ocean systems. His work spans operationally relevant applications—disaster science, flood and wildfire forecasting, public health impacts, and financial risk from weather—paired with hands-on model development including Fortran-based ESM modules. Trained at IIT Bombay and experienced across premier institutions in India and the U.S., he blends rigorous climate-modeling expertise with modern ML practice. Based in Bowling Green, Kentucky, he continues collaborative research as a Jackson School affiliate while teaching meteorology, reflecting a commitment to translating AI advances into societal resilience. A subtle through-line in his career is moving theory into practice: from phase-synchronization studies of ENSO–monsoon coupling to deployable high-resolution AI forecasting systems.
10 years of coding experience
10 years of employment as a software developer
Bachelor of Engineering (BE) Civil Engineering, Bachelor of Engineering (BE) Civil Engineering at Thapar Institute of Engineering & Technology
Diploma Earth System Sciences and Climate, Diploma Earth System Sciences and Climate at Indian Institute of Tropical Meteorology
Indian Institute of Technology Bombay
High School, High School at Rosary Senior Secondary School
English, Punjabi